https://github.com/thomaslecocq/msnoise-tomo
The Ambient Noise Tomography Plugin for MSNoise
https://github.com/thomaslecocq/msnoise-tomo
imaging noise passive python research seismic seismology signal-processing tomography volcanology
Last synced: 2 months ago
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The Ambient Noise Tomography Plugin for MSNoise
- Host: GitHub
- URL: https://github.com/thomaslecocq/msnoise-tomo
- Owner: ThomasLecocq
- License: eupl-1.1
- Created: 2017-03-02T14:02:33.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2021-05-01T23:45:06.000Z (about 4 years ago)
- Last Synced: 2025-03-26T10:52:17.383Z (3 months ago)
- Topics: imaging, noise, passive, python, research, seismic, seismology, signal-processing, tomography, volcanology
- Language: Python
- Homepage: http://www.msnoise.org
- Size: 1.81 MB
- Stars: 21
- Watchers: 1
- Forks: 16
- Open Issues: 17
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# MSNoise-Tomo
[](https://travis-ci.org/ThomasLecocq/msnoise-tomo)
[](https://ci.appveyor.com/project/ThomasLecocq/msnoise-tomo/branch/master)
MSNoise-Tomo is a plugin to the MSNoise framework, allowing to branch from the [REF stack](http://msnoise.org/doc/workflow/006_stack.html) to compute FTAN, dispersion curves and 2D period maps.
MSNoise-Tomo is developed by Thomas Lecocq (Royal Observatory of Belgium, ROB) based on original codes from A. Mordret and M. Landès (IPGP, 2013).
References
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* Mordret, A., Landès, M., Shapiro, N.M., Singh, S.C., Roux, P., Barkved, O.I., 2013. Near-surface study at the Valhall oil field from ambient noise surface wave tomography. Geophys. J. Int. 193, 1627–1643. https://doi.org/10.1093/gji/ggt061
* Barmin, M.P., Ritzwoller, M.H., Levshin, A.L., 2001. A Fast and Reliable Method for Surface Wave Tomography. Pure and Applied Geophysics 158, 1351–1375. https://doi.org/10.1007/PL00001225
Documentation
-------------
The documentation is available at http://msnoise.org/plugins/msnoise-tomo/doc/
Installation
------------
Create a new environment using conda:
* conda create -n tomo -c conda-forge python=3.7 obspy=1.1.1 msnoise shapely pyproj
* conda activate tomo
Then, the code can be installed from scratch using this repository, or using precompiled python wheels:
* Windows:http://msnoise.org/plugins/msnoise-tomo/msnoise_tomo-0.1b0-cp37-cp37m-win_amd64.whl
* Linux: http://msnoise.org/plugins/msnoise-tomo/msnoise_tomo-0.1b0-cp37-cp37m-linux_x86_64.whl
* MacOS:http://msnoise.org/plugins/msnoise-tomo/msnoise_tomo-0.1b0-cp37-cp37m-macosx_10_9_x86_64.whl
Remember, always consider the current GitHub *master* as not stable!
Commercial Usage
----------------
If you plan to use MSNoise-TOMO for commercial purposes, please contact Thomas
Lecocq directly.